Role overview
The micro-kernel architecture of Phoenix-RTOS architecture is the foundation on which we build high-performance and energy-efficient solutions for various embedded market segments.
You will join the Aerospace department, where the following projects are carried out:
Phoenix-SAT a framework dedicated to space applications, optimized for the use of AI/ML algorithms. The main goal of the project is to develop a platform that uses machine learning and artificial intelligence techniques to process and classify data collected from satellite sensors, particularly high-resolution optical and hyperspectral sensors. The key challenge will be ensuring the correct operation of the processing pipeline in a resource-constrained space environment, and in later stages, building solutions that enable model development directly on edge platforms operating in orbit.
Phoenix-PILOT a multi-domain autopilot project, particularly for unmanned aerial vehicles such as multirotor drones and fixed-wing aircraft. The primary objective is to develop autonomous applications for UAVs using ML/AI techniques based on image processing. Key challenges will include preparing object detection and classification models, as well as contributing to the development of decision-making algorithms.
What you'll work on
The person in this position will be responsible for creating and developing software related to the machine learning process, as well as integrating artificial intelligence solutions with other systems developed within the company. They will actively participate in research and development, design, and implementation work, thereby having a real impact on the shape of the software being produced. In particular, they will contribute to the development of Edge-IoT solutions by creating applications that support the automation of the machine learning process.
What we're looking for
- Experience in training deep learning models for computer vision.
- Knowledge of model compression techniques (quantization, pruning, distillation).